Please use this identifier to cite or link to this item:
Title: The Added Value of Real-World Evidence to Connect Disconnected Networks for Network Meta-Analysis: A Case Study in Rheumatoid Arthritis
Authors: Jenkins, D. A.
Martina, R.
Dequen, P.
Bujkiewicz, S.
Abrams, K.
First Published: 1-Nov-2016
Publisher: Elsevier for International Society for Pharmacoeconomics and Outcomes Research
Citation: Value in Health, 2016, 19 (7), pp. A393-A393 (1)
Abstract: Background: There are many circumstances under which networks of evidence may be ‘disconnected’ and network meta-analysis (NMA) cannot be conducted, unless additional assumptions are made. However, real-world evidence (RWE) which is becoming a more widely used source of clinical data to complement randomised evidence for relative effectiveness assessment, could help inform missing ‘connections’ within a network. We consider the impact of RWE on NMA to compare existing biologic DMARDS in rheumatoid arthritis (RA) for second-line therapy in a disconnected network. Methods: A literature search was undertaken to identify RCTs evaluating second-line biological therapies in RA. Patient data from two European registries were also accessed. Standard Bayesian NMA and naïve pooling of standard of care were applied and evaluated. Alternatively, RWE and RCT data were combined in an NMA to connect the RA network of studies. Results: Only 4 RCTs were identified for second-line biologics with one treatment (Golimumab) disconnected from the network. All methods applied were effective in allowing for the comparison of Golimumab against all other treatments. For example, Golimumab had increased probability of achieving remission by 7.6% (CI: 2.3% to 13.6%) compared to standard of care, an estimate that would not have been possible to obtain if using RCT data alone. The addition of RWE to the RCT data led to a decrease in the level of uncertainty of the probability of remission in Rituximab compared to standard of care from 8.3% (CI: 4.9% to 12%) to 7.2% (CI: 4.1% to 10.7%). Conclusion: The use of RWE was a useful approach here. By bridging disconnected networks of RCT evidence, RWE allowed evaluation of treatment options otherwise not comparable via a standard NMA of RCTs alone. In addition, estimates of effect of treatments already included in the RCT network were obtained with higher precision when including the RWE.
DOI Link: 10.1016/j.jval.2016.09.263
ISSN: 1098-3015
eISSN: 1524-4733
Version: Post-print
Status: Peer-reviewed
Type: Conference Paper
Rights: Copyright © Elsevier 2016. This version of the paper is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License (, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Description: Abstract only
Appears in Collections:Conference Papers & Presentations, Dept. of Health Sciences

Files in This Item:
File Description SizeFormat 
Jenkins+et+al+Abstract_ispor+2016+FINAL.pdfPost-review (final submitted author manuscript)415.91 kBAdobe PDFView/Open

Items in LRA are protected by copyright, with all rights reserved, unless otherwise indicated.